spacenet.point_patterns#

Pair correlation functions#

`cross_pair_correlation_function`	Computes the pair correlation function (PCF) or cross-pair correlation function (cross-PCF) for nodes in a spatial network.
`weighted_pair_correlation_function`	Computes the weighted pair correlation function between two populations of nodes.
`cross_weighted_pair_correlation_function`	Compute the cross weighted pair correlation function between two populations of objects (A and B) on a spatial network, where the contributions of each object to the pair correlation function are weighted by a kernel function based on their marker levels.

`helpers.spatial_bootstrap`	Compute the 95% confidence interval for the pair correlation function at each radius (and target marker, if applicable) using method of spatial bootstrap on spatial networks.
`helpers.polynomial_kernel`	Computes the polynomial kernel function for a given distance or array of distances.
`helpers.integrated_poly_finite_kernel`	Computes the integrated polynomial kernel function for given distances and bandwidth parameters.
`helpers.is_connected_filter`	A helper function to check if the network is connected and filter to the largest connected component if not.
`helpers.compute_contributions`	Computes the local contributions to the pair correlation function for a given reference node (object_id_A) and a set of target nodes (object_indices_B) at specified radii (r).
`helpers.compute_weighted_contributions`	Compute the local contributions to the pair correlation function for a given reference node (object_id_A) and a set of target nodes (object_indices_B) at specified radii (r), weighted by marker contributions.
`helpers.compute_contributions_parallel`	Runs the compute_contributions function in parallel across multiple CPU cores for a list of object indices.
`helpers.compute_weighted_contributions_parallel`	Computes the local contributions to the pair correlation function for a list of reference nodes (object_indices_A) and a set of target nodes (object_indices_B) at specified radii (r), weighted by marker contributions, in parallel across multiple CPU cores.